p8105_hw6_yx2450

##omit NA
nyc_inspections = read_csv("./data/DOHMH_New_York_City_Restaurant_Inspection_Results.csv.gz", 
                           col_types = cols(building = col_character()),
                           na = c("NA", "N/A")) %>% 
  na.omit() 

##clean dataset
nyc_inspections =
  nyc_inspections %>%
  filter(grade %in% c("A", "B", "C"), boro != "Missing") %>% 
  mutate(boro = str_to_title(boro),
         inspection_num = row_number()) %>% 
  select(inspection_num, boro, grade, score, critical_flag, dba, cuisine_description, zipcode, grade_date)

bar plot

##plot that shows the number of restaurant in different boros
nyc_inspections %>% 
  count(boro) %>% 
  plot_ly(x= ~boro, y = ~n, color = ~boro, type = "bar") %>% 
    layout(title = "Number of Restaurant in Different Boros",
      xaxis = list(title = "boro", tickangle = 45),
         yaxis = list(title = "number of restaurant"),
         margin = list(b = 100),
         barmode = 'group')

This bar plot describes the distribution of number of restaurant in different boros. The x axis represent different boros in NYC, and the y axis represent the number of restaurant.

boxplot

##plot that shows the score distribution of different cuisines
nyc_inspections %>% 
  filter(cuisine_description != "Not Listed/Not Applicable") %>% 
  mutate(cuisine_description = fct_reorder(cuisine_description, score)) %>%
  plot_ly(y = ~score, color = ~cuisine_description, type = "box",
          colors = "Set2") %>% 
  layout(title = "the Score Distribution of Different Cuisines",
         xaxis = list(title = "cuisine_description", tickangle = 90),
         yaxis = list(title = "score"),
         margin = list(b = 100),
         barmode = 'group',
         showlegend = FALSE)  

This box chart describes the distribution of scores of different cuisines. The x axis represents different cuisines, and the y axis shows the score distribution of each cuisines.

line plot

##plot that shows number of row for each grade date
nyc_inspections %>%
  separate(grade_date, into = c("year", "month", "day"), sep = "-") %>% 
  mutate(month = as.numeric(month)) %>%
  select(inspection_num: month) %>%
  count(year,month) %>% 
  mutate(date = str_c(year,month,"1",sep="-"),
         date = as.Date(date)) %>%
  arrange(date) %>% 
  plot_ly(x = ~date, y = ~n, type = "scatter", mode = "lines") %>% 
  layout(title = "the Number of Restaurant Graded on each Month",
         xaxis = list(title = "time"),
         yaxis = list(title = "number of restaurant"),
         margin = list(b = 100),
         barmode = 'group')

## Warning in as.POSIXlt.POSIXct(x, tz): unknown timezone 'zone/tz/2017c.1.0/
## zoneinfo/America/New_York'

This line plot describes how many restaurants were graded on each month. The x axis represents timeline, and the y axis represents number of restaurants was graded.